Immune dose computation for treatment plan optimization in radiotherapy

ABSTRACT

Methods for calculating the radiation dose to the immune system of a patient undergoing radiotherapy are provided. In particular, the methods provide for calculating an effective dose to blood (EDIC) to circulating immune cells. The methods can be incorporated into radiotherapy (RT) treatment planning systems, which are also provided. The methods can be used to optimize patient treatment plans. Methods for treating a patient with RT with an optimized treatment plan are provided.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is the National Stage of International PatentApplication No. PCT/US2018/030609, filed May 2, 2018, which claimspriority to U.S. Provisional Patent Application No. 62/630,015, filedFeb. 13, 2018, the contents of each of which are expressly incorporatedherein by reference in their entireties.

STATEMENT OF GOVERNMENT SUPPORT

This invention was made with government support under CA142840 awardedby the National Institutes of Health. The Government has certain rightsin the invention.

BACKGROUND

Radiotherapy (RT) is a major modality for cancer treatment. Inradiotherapy, the tumor and normal organs within the paths of radiationfields are often delineated in a computed tomography (CT) image, andradiation doses to the tumor and these organs at risk (OARs) arecalculated. Treatment plan optimization can be performed to maximize theradiation dose to the tumor while minimizing the dose to the OARS.

Recent reports suggest that radiation-induced tumor cell killing canactivate the immune system by releasing tumor specific antigens.Preclinical studies have demonstrated that the immune system plays a keyrole in tumor control during RT. Treatments with RT alone or RT combinedwith immunotherapy have been observed to control tumors inimmunocompetent mice, but not in immune-deficient mice. An abscopaleffect (i.e., shrinkage of un-irradiated tumors far apart from the RTfields) has been observed in animal studies and in a single-patient casereport. While these observations suggest that RT may augment anti-tumorimmunity in certain settings, RT is also well known to haveimmunosuppressive effects. One of the most common and clinicallysignificant features of radiation-induced immunosuppression isradiation-induced lymphopenia which has been repeatedly associated withpoorer survival in several studies as well as in a recent pooledanalysis of multiple treatment-refractory solid tumors.

Despite these observations, the immune system has not generally beenconsidered as an OAR.

SUMMARY

In a first aspect, described herein is a radiotherapy system comprisinga radiotherapy device configured to deliver a radiotherapy to a patientand a treatment controller having one or more processors and anon-transitory, tangible storage medium containing instructions that,when executed, cause the one or more processors to: calculate from aninitial radiotherapy treatment plan for a patient, an equivalent uniformdose (EUD) for each organ in a target irradiation area in the patient;calculate an effective dose of radiation to circulating immune cells inblood (EDIC) for the patient by summing all EUDs for all organs in thetarget irradiation area; and generate a new patient-specificradiotherapy treatment plan for the patient, wherein the newpatient-specific radiotherapy treatment plan decreases a calculated EDICrelative to the initial radiotherapy treatment plan, wherein theradiotherapy device is configured to deliver radiotherapy to the patientaccording to the new patient-specific radiotherapy treatment plan.

In some embodiments, the radiotherapy system of claim 1 furthercomprises one or more imaging modalities.

In some embodiments, the instructions, when executed, cause the one ormore processors to generate one or more additional new patient-specificradiotherapy treatment plans for the patient during delivery of the newpatient-specific radiotherapy treatment plan to the patient.

In a second aspect, described herein is a method for treating a patient,the method comprising: calculating from an initial radiotherapytreatment plan for the patient, an equivalent uniform dose (EUD) foreach organ in a target irradiation area in the patient; calculating aneffective dose of radiation to circulating immune cells in blood (EDIC)for the patient by summing all EUDs for all organs in the targetirradiation area; generating a new patient-specific radiotherapytreatment plan for the patient, wherein the new patient-specificradiotherapy treatment plan decreases a calculated EDIC relative to theinitial radiotherapy treatment plan; and delivering radiotherapy to thepatient according to the new patient-specific radiotherapy treatmentplan.

In some embodiments, the method for treating a patient further comprisesacquiring an image of the target irradiation area in the patientutilizing at least one imaging modality.

In some embodiments, the method for treating a patient further comprisesgenerating one or more additional new patient-specific radiotherapytreatment plans for the patient during delivery of the newpatient-specific radiotherapy treatment plan to the patient, stoppingdelivery of the new patient-specific radiotherapy treatment plan to thepatient, and delivering one of the one or more additional newpatient-specific radiotherapy treatment plans.

In a third aspect, described herein is a radiotherapy system comprisinga radiotherapy device configured to deliver radiotherapy in accordancewith a radiotherapy plan and one or more processors programmed toperform a method for treating a patient described herein.

In a fourth aspect, described herein is non-transitory computer-readablemedium having instructions stored thereon for causing one or moreprocessors to perform

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flowchart illustrating a method according to one embodiment.

FIG. 2 is a flowchart illustrating a method according to one embodiment.

FIG. 3 is a flowchart illustrating a method according to one embodiment.

FIG. 4 is a flowchart illustrating a method according to one embodiment.

FIG. 5 is a block diagram illustrating a system formed in accordancewith one embodiment that may be used to carry out the methods describedherein.

FIG. 6A depicts overall survival curves for patients divided into fourquartiles according to the effective radiation dose to circulatingimmune cells (EDIC), in accordance with embodiments of the disclosure.

FIG. 6B depicts overall survival curves for patients divided into sixEDIC groups according to absolute EDIC values with a 1.5-Gydose-increment, in accordance with embodiments of the disclosure.

FIG. 7A depicts the relationship between relative hazard of death andEDIC, in accordance with embodiments of the disclosure.

FIG. 7B depicts the relationship between two-year overall survival rateand EDIC by normal tissue complication probability (NTCP) survival mode,in accordance with embodiments of the disclosure.

FIGS. 8A and 8B depict graphs demonstrating the variation in equivalentuniform dose (EUD) to the total blood as a function of the fractionnumber (n) for various V % (the percentage blood volume irradiated ineach fraction for a specific organ), which contains B % of blood volumeand received irradiation with a mean organ dose (MOD).

FIG. 8C depicts the difference in EUD between an EUD model and theactual EUD as determined from the DVH, in accordance with embodiments ofthe disclosure.

FIG. 9 is a schematic representation of the major organs in thecirculatory system and their estimated percentage of cardiac output (A%) and percentage of blood volume (B %) according to established anatomyand physiology data.

FIG. 10 is an illustration depicting the defined parameters of:percentage of cardiac output (A %); and percentage of blood volume (B%), in accordance with embodiments of the disclosure.

FIG. 11 depicts a graph demonstrating a relationship between dose losingfactor k₁ and V %, in accordance with embodiments of the disclosure.

FIG. 12 depicts a graph demonstrating a relationship between thefraction number at which saturation occurs and V %, in accordance withembodiments of the disclosure.

FIG. 13 depicts a graph demonstrating a relationship between thesurvival rate and mean lung dose (MLD), in accordance with embodimentsof the disclosure.

While the disclosed subject matter is amenable to various modificationsand alternative forms, specific embodiments are described herein indetail. The intention, however, is not to limit the disclosure to theparticular embodiments described. On the contrary, the disclosure isintended to cover all modifications, equivalents, and alternativesfalling within the scope of the disclosure as defined by the appendedclaims.

Similarly, although illustrative methods may be described herein, thedescription of the methods should not be interpreted as implying anyrequirement of, or particular order among or between, the various stepsdisclosed herein. However, certain embodiments may require certain stepsand/or certain orders between certain steps, as may be explicitlydescribed herein and/or as may be understood from the nature of thesteps themselves (e.g., the performance of some steps may depend on theoutcome of a previous step). Additionally, a “set,” “subset,” or “group”of items (e.g., inputs, algorithms, data values, etc.) may include oneor more items, and, similarly, a subset or subgroup of items may includeone or more items. A “plurality” means more than one.

As the terms are used herein with respect to ranges, “about” and“approximately” may be used, interchangeably, to refer to a measurementthat includes the stated measurement and that also includes anymeasurements that are reasonably close to the stated measurement, butthat may differ by a reasonably small amount such as will be understood,and readily ascertained, by individuals having ordinary skill in therelevant arts to be attributable to measurement error, differences inmeasurement and/or manufacturing equipment calibration, human error inreading and/or setting measurements, adjustments made to optimizeperformance and/or structural parameters in view of differences inmeasurements associated with other components, particular implementationscenarios, imprecise adjustment and/or manipulation of objects by aperson or machine, and/or the like.

DETAILED DESCRIPTION

Certain embodiments described herein provide methods for calculating theradiation dose to the immune system of a patient undergoingradiotherapy. In some embodiments, the methods described herein can beincorporated into radiotherapy (RT) treatment planning systems, whichare also provided herein. In some embodiments, the methods describedherein can be used to optimize patient treatment plans. Also providedare methods for treating a patient with RT with an optimized treatmentplan.

As discussed below in more detail, portions of these methods can beimplemented using a processor executing software stored in a tangible,non-transitory storage medium. For example, the software could be storedin the long-term memory (e.g., solid state memory) in a radiotherapysystem, executed by the processor(s) in the radiotherapy system. Inother embodiments, the software could be stored in a separate system.

The immune system has largely not been considered as an organ at riskfor RT toxicity, and no guidelines presently exist to delineate theimmune system for the purposes of RT planning. In certain embodiments,the immune system is defined as a composition of six substructures: 1)immune cells in the lymph nodes and parenchyma in the organ of the tumorsite; such as in lung lymph nodes and lung parenchyma for lung cancer;2) immune cells in the circulating blood; 3) immune cells in the lymphnodes and other major lymphatic organs in the other parts of the body,including lymphatic ducts and spleen; 4) T-cells in the thyme; 5) Bonemarrow; and 6) tumor infiltrating immune cells within the tumor. Asdescribed herein, the radiation dose to the immune system is a keypredictor for success of treatment. While the immune cells in 5 of the 6substructures are relatively stable during irradiation, the immune cellsin the circulating blood are not stable. Calculating the radiation doseadministered to this substructure is very difficult.

To date, few examples of methods for calculating the radiation dosereceived by the immune system during RT exist. One method, described byEllsworth et al. (US Pat. Pub. No. 2016/0339270), determines a dosereceived by circulating blood as the dose to the immune system duringRT. The method predicts a radiation dose received by the circulatingblood by assuming the blood has a similar known flow rate in anirradiating site that includes a tumor and surrounding normal tissues,determining a dose of radiation delivered to the site in a patient,generating a three-dimensional dose grid for the site, using thethree-dimensional dose grid for the site to calculate a distribution ofradiation dose to a blood pool that is either within or transits throughthe site, generating dose volume histograms for the blood or itsconstituents as normal organs; and indicating the dose of radiationreceived by circulating blood using the quantification.

The method of Ellsworth et al. assumes that the blood concentration andflow rate through the irradiating site that includes the tumor andsurrounding normal tissue are the same. However, the blood concentrationand flow rate through the various organs and vessels in the irradiatingsite vary considerably. As described herein, the blood concentration andflow rate are important determinants of the radiation absorbed by thecirculating immune cells in blood. In addition, the immune system alsoincludes other substructures than the circulating immune cells in blood.Thus, the present disclosure provides improved methods to moreaccurately determine the radiation dose received by the circulatingimmune cells in blood and immune system during RT. Furthermore,described herein for the first time are methods for identifying aradiation dose to the immune system that can improve overall survival ofpatients receiving radiotherapy.

Certain embodiments provide methods for calculating an effective dose ofradiation to circulating immune cells in blood (EDIC) in a patient. Asdepicted in FIG. 1, in some embodiments, method 100 for calculating theEDIC comprises first calculating an equivalent uniform dose (EUD) 102 tothe total blood after n fractions as a result of circulating through anorgan and/or vascularized tumor in a target irradiation area includingone or more tumors in the patient and then summing all calculated EUDs102 for the target irradiation area. The target irradiation areaincludes the tumor that is being targeted by RT, as well as varioussurrounding normal organs in the pathway of the irradiating fields. Forexample, in an embodiment where the lungs are to be treated by R, theorgans to be included in the target irradiation area include the lungs,the heart, the large vessels of the thoracic region, and the smallvessels and capillaries of the tumor and other organs in the thoracicregion. In this example, the EDIC is calculated 104 by summing thecalculated EUDs for the total blood circulating through the lungs,heart, large vessels of the thoracic region, and the small vessels andcapillaries of the tumor and other organs in the thoracic region (seealso FIG. 3).

In some embodiments, the EUD to the total blood circulating through eachorgan and/or vascularized tumor can be calculated as described byNiemierko (Med Phys, 1997, 24(1):103-110), which is hereby incorporatedby reference in its entirety, and can be calculated directly from thecorresponding dose-volume histograms (DVHs).

In certain embodiments, a novel method for calculating the EUD for eachorgan and/or vascularized tumor is used. As depicted in FIG. 2,according an embodiment 200, the DVH of the total circulating blood (orimmune cells in the circulating blood) due to irradiation of an organ isfirst determined 202. To determine the DVH, it is assumed that theirradiation uniformly delivers a dose (d) to the portion of blood thatpasses through the organ during a treatment fraction, which account forV % of the total circulating blood. V % is calculated by:V%=B%+(A%−B%)*t/T,  (1)wherein the organ has 1) a cardiac output A %, which is defined as theamount of blood branching into the organ as a percentage of the totalblood flow out of the heart, and 2) a percentage blood volume B %, whichis defined as the amount of blood contained in the organ at any timerelative to the total body blood volume, that the time for completingone blood circulation is T, and the irradiation time is t. Thesedefinitions of A % and B % are illustrated by FIG. 10, which depicts atheoretical organ having a cardiac output A % and a percentage bloodvolume B %. The dose delivered to V % is given by:

$\begin{matrix}{{d = {\left( \frac{MOD}{n} \right)*\left( \frac{B}{V} \right)}},} & (2)\end{matrix}$wherein the number of radiotherapy fractions is n, and the organ hasreceived a mean organ dose of MOD. In certain embodiments, it is assumedthat after each irradiation, the irradiated immune cells are uniformlyredistributed before the next radiotherapy fraction is delivered. Thus,the differential DVH after ith fraction can be derived by calculatingV(i,j), which is the percentage of blood volume that receives a dose ofj*d. Initially, V(0,0)=100%.

After the 1^(st) fraction, V(1,1)=V %*V(0,0), and V(1,0)=(1−V %)*V(0,0).

After the 2^(nd) faction, V(2,2)=V %*V(1,1), V(2,1)=V %*V(1,0)+(1−V%)*V(1,1) and V(2,0)=(1−V %)*V(1,0).

After n^(th) fraction, V(n,n)=V %*V(n−1,1), V(n, n−1)=V%*V(n−1,n−2)+(1−V %)*V(n−1,n−1), . . . V(n,1)=V %*V(n−1,0)+(1−V%)*V(n−1,1), and V(n,0)=(1−V %)*V(n−1,0).

In some embodiments, the equivalent uniform dose (EUD) to the totalblood occurring as a result of irradiation of an organ within the targetirradiation area is calculated from the differential DVH 204. In certainembodiments, known algorithms can be used to calculate the EUD from thedifferential DVH. For example, the EUD can be calculated by:EUD_(n)=[Σ_(j) V(n,j)*(d*j)^(a)]^(1/a),  (3)(Niemierko (Med Phys, 1997, 24(1):103-110)). The EDIC can then becalculated 206 by summing all calculated EUDs for the irradiation area.

In some embodiments, the EUD of the blood contributed by a givenblood-containing organ can be calculated for various V %. As depicted byFIG. 8A, the calculated EUD varies with fraction number n for various V% for an exemplary organ with B %*MOD=3 Gy. FIG. 8A demonstrates thatwhen n>2.4/V %, the EUD starts to become saturated, indicating that theentire blood volume becomes irradiated when the number of fractions (n)is sufficiently large.

In some embodiments, the EUD can be approximated by an analytical model:

$\begin{matrix}{{{EUD} = {{B\%*{MOD}*k_{1}\mspace{14mu}{when}\mspace{14mu} n} > k_{2}}},{or}} & \left( {4a} \right) \\{{{EUD} = {{B\%*{MOD}*k_{1}*\left( \frac{n}{k_{2}} \right)^{\frac{1}{2}}\mspace{14mu}{when}\mspace{14mu} n} < k_{2}}},} & \left( {4b} \right)\end{matrix}$wherein k₁ and k₂ depend on V %. k₁ is a dose losing factor, and k₁ canbe approximated by k₁=1+0.0031*ln(V %)/V % (see FIG. 11). k₂ is asaturation fraction factor, and can be approximated by k₂=2.4/V % (seeFIG. 12). FIG. 8B depicts the difference in EUD between the EUD model of(4a) and (4b), and the actual EUD as determined from the DVH. Asdemonstrated by FIG. 8B, the models provide an excellent determinationof EUD.

In some embodiments, the EUD can be alternatively approximated by otheranalytical models such as:

$\begin{matrix}{{{EUD} = {{B\%*{MOD}*k_{1}\mspace{14mu}{when}\mspace{14mu} n} > k_{2}}},{and}} & {\;\left( {5a} \right)} \\{{{{EUD} = {{{B\%*{MOD}*k_{1}} + {0.8*{\ln\left( \frac{n}{k_{3}} \right)}\mspace{14mu}{when}\mspace{14mu} n}} < k_{2}}},}\mspace{11mu}} & \left( {5b} \right)\end{matrix}$wherein k₁=1+0.0031*ln(V %)/V %, as described above, and k₃ is asaturation fraction factor, and can be approximated by k₃=2.8/V %. FIG.8C depicts the difference in EUD between the EUD model of (5a) and (5b),and the actual EUD as determined from the DVH. As demonstrated by FIG.8C, the models provide an excellent determination of EUD.

In some embodiments, the saturation fraction factor is related to thenumber of radiation fractions required to saturate the EUD, indicatingthat the entire blood volume becomes irradiated. In certain embodiments,the saturation fraction factor is the quotient of a numerator of 2 to 3and a denominator equal to V %. As provided above, in some embodiments,the saturation fraction factor k₂=2.4/V %. In some embodiments, thesaturation fraction factor k₃=2.8/V %.

FIG. 3 illustrates the EDIC calculation for a patient in which the lungsare to be treated (i.e., thoracic radiation). The EUD for each of thelungs 302, heart 304, thoracic great vessels 306, and thoracic smallvessels and capillaries 308 is first calculated, and then summed todetermine the EDIC 310.

In some embodiments, an EDIC for a proposed or prospective RT treatmentplan can be calculated. The EDIC for a RT treatment plan selected for apatient that is scheduled to undergo RT treatment can be calculatedprior to treatment to determine the radiation dose to be administered tothe patient. Depending on the calculated EDIC, treatment can proceedaccording to the selected treatment plan, the selected treatment plancan be optimized, or a new treatment plan can be selected. Methods forselecting and/or optimizing an initial RT treatment plan are providedherein. In other embodiments, an EDIC for an RT treatment plan alreadyadministered to a patient can be calculated.

The values for A % and B % for various organs for use according to someembodiments are provided in Table 1, and depicted in FIG. 9. In otherembodiments, the values for A % and B % can be calculated based on knownpopulation data. In some embodiments, the values for A % and B % can becalculated for a patient based on the patient's specific anatomy. Insome embodiments, information on the patient's specific anatomy can beprovided by one or more imaging modalities, including, for example,computed tomography (CT) scanners, positron emission tomography (PET)scanners, magnetic resonance (MR) scanners, single photon emissioncomputed tomography (SPECT) scanners, and the like.

TABLE 1 Organ A% (% cardiac output) B% (% total blood volume) Brain 16 8Upper Body 20 10 Lungs (total) 100 12 Lung (each) 50 6 Heart 100 8Digestive System 20 10 Liver 6 13 Kidneys 22 11 Lower Body 16 8 GreatVessels 30-60 Dependent on contoured volume

Returning to the example of thoracic radiation, the organs/componentsthat are irradiated mainly include 1) the lungs, 2) the heart, 3) thegreat vessels, and 4) small vessels and capillaries in other organs,such as the esophagus, muscles, bones, and skin. The total dose to thecirculating immune cells resulting from thoracic radiation can beconsidered as the sum of EUDs to the total blood contributed by thesefour organs/components. Assuming T˜1 min, t>1 min, and n≥30 (as mostconventional definitive radiotherapy requires more than 30 fractions,EUD to total blood can be reliably calculated as B %*MOD for lung hear,and great vessels, because of their large cardiac outputs (A % is 50%for each lung, 100% for heart, >30% for the great vessels). B % is 12%for lung, 8% for heart, 45%-50% for the great vessels, and 30%-40 forthe small vessels and capillaries in other organs. For the 4^(th)component (small vessels and capillaries in other organs), V % can beestimated as being 6-8%. Thus k₁˜0.85, k₂˜45, and EUD to the total bloodcan be estimated using equation 4. It can be assumed that the vesselsand capillaries are uniformly distributed in the body, so that integraltotal body dose can be used to replace the MOD for the large vessels aswell as the 4^(th) component (i.e., small vessels and capillaries inother organs). Therefore, the EDIC, as the sum of EUD contributions ofthe 4 components, is expressed as:

$\begin{matrix}{{{EDIC} = {{B_{1}\%*{MLD}} + {B_{2}\%*{MHD}} + {\left\lbrack {{B_{3}\%} + {B_{4}\%*k_{1}*\left( \frac{n}{k_{2}} \right)^{\frac{1}{2}}}} \right\rbrack*{{ITD}/\left( {6{1.8}*10^{3}} \right)}}}},} & (6)\end{matrix}$wherein MLD, MHD, and ITD are mean lung dose, mean heart dose, andintegral total dose, respectively, and 61.8*10³ (cm³) is the averagetotal body volume, assuming average weight and density of 70 lps/63 kgand 1.02 g/cm³.

Alternatively, in the thoracic RT example, the EUD to the total bloodresulting from circulation through the large vessels can be calculatedas

${{EUD} = {\frac{V_{GV}}{5000}*{MVD}}},$wherein V_(GV)/5000 is the percentage blood volume in the contouredgreat vessels, with V_(GV) as the volume of contoured great vessels incubic centimeters and 5000 as the total blood volume, giving:

$\begin{matrix}{\left. {{EDIC} = {{B_{1}\%*{MLD}} + {B_{2}\%*{MHD}} + {\frac{V_{GV}}{5000}*{MVD}} + {B_{4}\%*k_{1}*\left( \frac{n}{k_{2}} \right)^{\frac{1}{2}}}}} \right\rbrack*{{ITD}/\left( {6{1.8}*10^{3}} \right)}} & (7)\end{matrix}$

The EDIC calculation for a thoracic radiotherapy is provided merely asan example. It will be recognized that an EDIC can be calculated forother target irradiation areas, including those irradiated during thetreatment of, for example, brain cancer, non-melanoma skin cancer, headand neck cancer, breast cancer, cervical cancer, rectal cancer, livercancer, pancreatic cancer, and prostate cancer. In such targetirradiation areas, the EUDs to the blood circulating through theirradiated organs and/or other components can be calculated from adifferential DVH for each of the organs and/or other components, or canbe approximated as provided by either equation 4 or 5. Necessaryassumptions, such as those made for the small vessels and capillaries inthe thoracic RT example, will be recognized by those of skill in art,and are within the scope of the present disclosure. For example, for atumor in the pancreas, the radiation will potentially pass through theliver, the kidney, the digestive system, the great vessels, and all theother organs. The mean organ dose for these organs can be calculated,the A % and B % of these organs can be determined according to table 1,and based on the estimated irradiation time for each fraction, we candetermine the V % for each organ, thus an estimated EDIC can becalculated using EQ. 6 or EQ. 7.

The parameters provided by Table 1, EQs. 6 and 7, such as B1%, B2%, B3%,B4%, 5000 (ml) for the total blood volume, and 61.8*10³ for the bodymass can be individualized for different patients according to theirweight, and volumes as determined by their CT image.

It is described herein for the first time that there is a relationshipbetween EDIC as calculated by the methods described herein, and overallsurvival; hazard rates increase with increasing EDIC when EDIC is lessthan 6.0 Gy or larger than 8.0 Gy. The curve is relatively flat whenEDIC is between 6.0 Gy and 8.0 Gy.

In certain embodiments, an RT treatment plan resulting in a predictedEDIC of 6.0 Gy or less is selected for a patient. The RT treatment planresulting in a predicted EDIC of 6.0 Gy or less can be selected from aplurality of potential RT treatment plans. In certain embodiments, theRT treatment plan having the lowest EDIC is selected. In otherembodiments, the RT treatment plan having the best predicted outcomewhile maintaining an EDIC of 6.0 Gy is selected. In certain embodiments,RT is administered to a patient according to the selected RT treatmentplan.

Certain embodiments provide methods for generating a patient-specificradiotherapy treatment plan. FIG. 4 illustrates a general method 400 forgenerating a patient-specific radiotherapy treatment plan. An initial RTtreatment plan for a patient is provided 402. An EUD for each organ inthe target irradiation area based on the initial RT treatment plan isthen calculated 404, and the EDIC is calculated 406 by summing all EUD'scalculated for the target irradiation area. Based on the EDIC, theinitial RT treatment plan is then adjusted or otherwise optimized 408.

In some embodiments, a patient-specific RT treatment plan can begenerated. In some embodiments, a new patient-specific RT treatment planis generated. In certain embodiments, a new patient-specific RTtreatment plan is generated by adjusting or otherwise optimizing aninitial RT treatment plan preselected for a patient. In certainembodiments, the initial RT treatment plan is adjusted to reduce thecalculated EDIC and generate a new patient-specific RT treatment planwith a lower calculated EDIC. In some embodiments, any reduction in EDICcan have an impact on overall survival. In some embodiments, the newpatient-specific RT treatment plan has a calculated EDIC of 6.0 Gy orless. In other embodiments, the new patient-specific RT treatment planmaximizes the radiation dose while maintaining a calculated EDIC of 6.0Gy or less. The EDIC for any particular RT treatment plan can becalculated as provided herein, where the treatment parameters of aparticular RT treatment plan are incorporated into the EDIC calculation.

In certain embodiments, a new patient-specific RT treatment plan havinga reduced calculated EDIC relative to an initial RT treatment plan canbe generated by, for example, reducing circulating blood exposure viahypofractionated treatment regimens and/or decreasing the radiationdelivery time (i.e., increasing the dose rate) relative to the initialRT treatment plan; adjusting beam energies and directions, number ofbeams, and/or collimator margins relative to the initial RT treatmentplan, and/or using intensity modulated radiotherapy (IMRT) and othersimilar advanced planning techniques such as volumetric modulated arctherapy (VMAT); using advanced RT technology such as, for example, imageguided adaptive therapy and proton therapy; and dose de-escalation andmargin reduction relative to the initial RT treatment plan. Suchtechniques can reduce the calculated EDIC relative to the initial RTtreatment plan, and may thus improve overall survival of patientsundergoing radiotherapy treatment using a new patient-specific RTtreatment plan determined according to the methods of the disclosure.

In other embodiments, a new patient-specific RT treatment plan maximizesthe radiation does delivered to a tumor while minimizing the dose to thecirculating immune cells (i.e., minimizing EDIC). In some embodiments,such optimization may necessitate increasing the calculated EDIC inorder to maximize the radiation dose delivered to a tumor. Any increasein the dose to the circulating immune cells must be weighed against anybenefit derived from maximizing the radiation dose to the tumor. In someembodiments, the new patient-specific RT treatment plan is set so thatthe calculated EDIC increases, but does not exceed 6.0 Gy. This may bedesirable to allow for maximization of the radiation dose to a tumorwhile minimizing the risks associated with higher doses beingadministered to the circulating immune cells. The EDIC can be increasedby, for example, increasing the radiation delivery time, adjusting beamenergies and directions, the number of beams, and collimator margins,and dose escalation and increasing margins.

In some embodiments, the radiation dose to the immune cells in the lymphnodes and parenchyma of the site of the tumor can be surrogated by theradiation dose to the organ of the tumor site, or the dose to thelymphatic stations in the site. For example, for lung tumors, the doseto the lung or the dose to the lung lymphatic station can be thesurrogate for the radiation dose to the immune cells in the lymph nodes.

In some embodiments, the radiation dose to the tumor infiltrating immunecells within the tumor can be determined as D=D₀−T_(a), wherein the D₀is the prescription dose to the tumor, and T_(a) is the dose that beginsto activate the anti-tumor immunity.

In some embodiments, the radiation dose to the immune cells in the lymphnodes and other major lymphatic organs in the other parts of the bodycan be determined by directly delineating the structures (lymphaticducts, spleen, etc.) in a patient's CT images and calculating the doseto the structures.

In some embodiments, the radiation dose to the T-cells in the thyme canbe determined by directly delineating the thyme structure in a patient'sCT image and calculating the dose to the thyme.

In some embodiments, the radiation dose to the bone marrow can bedetermined by directly delineating the bone structure in a patient's CTimage and calculating the dose to the structure.

It is described herein for the first time that the relationship ofoverall survival (OS) and mean lung dose (MLD) can be modeled by anormal tissue complication probability (NTCP) model with D₅₀=15 Gy, andthe OS did not go to 0% when MLD further increased (FIG. 13). AlthoughMLD has been reported to be associated with OS, it was previouslybelieved that the lung toxicity was the underlying mechanism of thisassociation. However, the fatal lung toxicity usually occurred when lungdoses were much higher (e.g., it has been reported that D₅₀ of MLD forgrade 2 toxicity was about 30 Gy). The OS-MLD relationship is wellexplained by the radiation damage of the immune cells in the lung lymphnodes and lung parenchyma. The immune cell pools in blood and othersubstructures may provide continuous flow to the site, so that the OSdid not go to 0%.

In certain embodiments, methods are provided for determining adose-volume histogram (DVH) for the total circulating blood (or immunecells in the circulating blood). In some embodiments, the DVH for theimmune cells in the circulating blood is determined as provided herein.While in certain embodiments the DVH for the immune cells is firstdetermined in order to provide for the calculation of the equivalentuniform dose (EUD) to the immune cells in the circulating blood, inother embodiments no EUD is calculated, and the DVH for the immune cellsin the circulating blood can be utilized as a radiotherapy treatmentplan evaluation tool. In certain embodiments, the DVHs for two or moredifferent radiotherapy treatment plans are determined and evaluated. Theradiotherapy treatment plan providing a desired radiation dosedistribution to the immune cells in the circulating blood can then beselected.

In some embodiments, the methods for calculating the effective dose toimmune cells (EDIC) resulting from RT or a particular RT treatment planare carried out on one or more suitably programmed computers. In someaspects, methods for calculating the EDIC and optimizing an RT treatmentplan based on the calculated EDIC are carried out on a radiotherapysystem. FIG. 5 illustrates a radiotherapy system 500 formed inaccordance with an embodiment that can be used to carry out the methodsdisclosed and described herein. For example, the system 500 can be usedto carry out the methods, including methods 100 (FIG. 1), 200 (FIG. 2),300 (FIG. 3), and 400 (FIG. 4). In some embodiments, the methods can beautomated by the system 500. In some embodiments, certain steps of themethods can be automated by the system 500 while others may be performedmanually or otherwise require user interaction. In some embodiments, theuser provides an initial treatment plan for a patient to the system 500,or otherwise causes an initial treatment plan to be provided to thesystem 500, and the system 500 automatically calculates the EDIC for theprovided initial RT treatment plan and optimizes the initial RTtreatment plan according to the methods described herein in accordancewith pre-selected treatment criteria (e.g., reducing EDIC, or maximizingradiation dose to a tumor while minimizing EDIC to a predeterminedrange). In some embodiments, radiotherapy system 500 is an integratedstandalone system that is located at one site. In other embodiments, oneor more components of the system are located remotely with respect toeach other. For example, in some embodiments, the EDIC calculator 510,treatment plan optimizer 512, database(s) 514, and storage system 518may be implemented in multiple instances, distributed across multiplecomputing devices, instantiated within multiple virtual machines, andthe like.

As depicted, the radiotherapy system 500 comprises a radiotherapy device502; a treatment controller 504 comprising a user interface 506, aradiotherapy device controller 508, an EDIC calculator, and a treatmentplan optimizer; one or more databases 514; one or more input/output(I/O) devices 516, and a storage system 518. In some embodiments, thedatabase 514 provides past or proposed (i.e., initial) RT treatmentplans and/or patient records to the treatment controller 504.

FIG. 5 provides a block diagram of a treatment controller 504 accordingto one embodiment. In some embodiments, the treatment controller 504 cancalculate the EDIC for a provided RT treatment plan and/or control aradiotherapy device according to an optimized RT treatment plan. In someembodiments, the treatment controller 504 comprises a system controller520, a user interface 506, a radiotherapy (RT) device controller 508, anEDIC calculator 510, and a treatment plan optimizer 512. The systemcontroller 520 is communicatively coupled to the user interface 512and/or the radiotherapy device 502. In some embodiments, the systemcontrol 520 comprises one or more processors/modules to calculate EDICsfor particular treatment plans and, optionally, optimize the treatmentplans in accordance with the methods described herein. For example, insome embodiments, the system control 520 includes one or more modules,each module being configured to execute a set of instructions that arestored in one or more storage elements (e.g., instructions stored on atangible and/or non-transitory computer readable storage medium) tocalculate EDICs and, optionally, optimize the treatment plan. In someembodiments the set of instructions includes various commands thatinstruct the system controller 520 as a processing machine to performspecific operations such as the processes and methods described herein.

As illustrated, the treatment controller 504 comprises a plurality ofmodules or submodules that control operation of the system controller520. In some embodiments, the treatment controller 504 includes modules508, 510, and 512, which are connected to or form a part of the systemcontroller 520, and are connected to a storage system 518 and one ormore databases 514. The storage system 518 and databases 514 cancommunicate with at least some of the modules 508, 510, 512, and systemcontroller 520. In some embodiments, the modules comprise a radiotherapydevice controller 508, an EDIC calculator 510, and a treatment planoptimizer 512. In some embodiments, the radiotherapy system 500comprises additional modules or sub-modules, configures to perform theoperations and methods described herein.

The EDIC calculator 510 is configured to receive an initial RT treatmentplan, and optionally patient-specific anatomical information, from thedatabase 514 or from the I/O device 516, and to calculate the EDIC fromthe RT treatment plan and optional patient-specific anatomicalinformation according to the methods described herein.

The treatment plan optimizer 512 is configured to optimize a treatmentplan, or otherwise select a treatment plan, according to the methodsdescribed herein.

The radiotherapy device controller 508 is configured to receive anoptimized or otherwise selected treatment plan from treatment planoptimizer 512, and to control radiotherapy device 502. The radiotherapydevice controller 508 is configured to cause the radiotherapy device 502to administer a radiotherapy according to an optimized or otherwiseselected radiotherapy treatment plan.

By way of example, the treatment controller 504 can be or include adesktop computer, a laptop computer, a notebook computer, a tabletcomputer, a smart phone, and the like. In some embodiments, the userinterface 506 includes hardware, firmware, software, or a combinationthereof that enables a user to directly or indirectly control operationof the system controller 520 and the various other modules and/orsub-modules. In some embodiments, the radiotherapy system 500 comprisesan input/output (I/O) device 514, such as a keyboard, display printer,disk drive, universal serial bus (USB) port, a speaker, pointer device,trackball, button, switch, touch screen, and the like.

In some embodiments, the radiotherapy system 500 displays the initial RTtreatment plan and the resulting optimized or selected RT treatment planon an I/O device 516 that is a display. In other embodiments, theradiotherapy system 500 is configured to deliver a selected or optimizedRT treatment plan to a printer, and email address, or other output.

In some embodiments, the radiotherapy system 500 comprises only thosecomponents necessary to select or optimize an RT treatment plan. Forexample, in some embodiments, the radiotherapy device 502 and theradiotherapy device controller 508 are excluded. Thus, in someembodiments, a radiotherapy treatment controller is provided. Theradiotherapy treatment controller can be the same as the treatmentcontroller 504 described above.

In some embodiments, a radiotherapy system 500 also includes one or moreimaging modalities suitable for acquiring images of areas of interest,such as a target irradiation area within a patient. Suitable imagingmodalities include, for example, computed tomography (CT) scanners,positron emission tomography (PET) scanners, magnetic resonance (MR)scanners, single photon emission computed tomography (SPECT) scanners,and the like. In some embodiments, the images acquired by the imagingmodalities are three-dimensional images. In other embodiments, theimages are two-dimensional. In certain embodiments, three-dimensionalimages include a stack of two dimensional images (i.e., slices). In someembodiments, the one or more imaging modalities are configured toprovide patient-specific anatomical information to the treatmentcontroller 504 or one of its components (e.g., EDIC calculator 510).

As used herein, the terms “module,” “system,” and “system controller”can refer to a hardware and/or software system and circuitry thatoperates to perform one or more functions. A module, system, or systemcontroller may include a computer processor, controller, or otherlogic-based device that performs operations based on instructions storedon a tangible and non-transitory computer readable storage medium, suchas a computer memory. Alternatively, a module, system, or systemcontroller can include a hard-wired device that performs operationsbased on hard-wired logic and circuitry. The module, system, or systemcontroller depicted in FIG. 5 can represent the hardware and circuitrythat operates based on software or hardwired instructions, the softwarethat directs hardware to perform the operations, or a combinationthereof. The module, system, or system controller can include orrepresent hardware circuits or circuitry that include and/or areconnected with one or more processors, such as one or more computermicroprocessors.

As used herein, the terms “software” and “firmware” are interchangeable,and include any computer program stored in memory for execution by acomputer, including Random Access Memory (RAM), Read Only Memory (ROM),Electronically Erasable Programmable Read Only Memory (EEPROM),non-volatile RAM (NVRAM), flash memory, optical or holographic media,magnetic cassettes, magnetic tape, magnetic disk storage or othermagnetic storage devices, data transmissions, or any other medium thatcan be used to store information and can be accessed by a computingdevice. The above memory types are representative only, and are thus notlimiting as to the types of memory usable for storage of a computerprogram.

In some embodiments, a processing unit, processor, module, or computingsystem that is “configured to” perform a task or operation can beunderstood as being particularly structured to perform the task oroperation (e.g., having one or more programs or instructions storedthereon or used in conjunction therewith tailored or intended to performthe task or operation, and/or having an arrangement of processingcircuitry tailored or intended to perform the task or operation). Ageneral purpose computer (which may become “configured to” perform thetask or operation if appropriately programmed) is not “configured to”perform a task or operation unless or until specifically programmed orstructurally modified to perform the task or operation.

In some embodiments, the memory stores computer-executable instructionsfor causing the system controller 520 to implement aspects ofembodiments of system components discussed herein and/or to performaspects of embodiments of methods and procedures discussed herein.Computer-executable instructions may include, for example, computercode, machine-useable instructions, and the like such as, for example,program components capable of being executed by one or more processorsassociated with a computing device. Program components may be programmedusing any number of different programming environments, includingvarious languages, development kits, frameworks, and/or the like. Someor all of the functionality contemplated herein may also, oralternatively, be implemented in hardware and/or firmware.

In some embodiments, elements of the radiotherapy system 500, such asthe treatment controller 504 and modules or sub-modules thereof,database(s) 514, I/O device(s) 516, storage system 518, and radiotherapydevice 502 are communicatively coupled by one or more communicationlinks. In some embodiments, the one or more communication links can be,or include, a wired communication link such as a USB link, a proprietarywired protocol, and the like. The one or more communication links canbe, or include, a wireless communication link such as a short-rangeradio link, such as Bluetooth IEEE 802.11, a proprietary wirelessprotocol, and the like.

The term “communication link” can refer to an ability to communicatesome type of information in at least one direction between at least twoelements of a computer system, and should not be understood to belimited to a direct, persistent, or otherwise limited communicationchannel. That is, according to some embodiments, the communication linkmay be a persistent communication link, an intermittent communicationlink, an ad-hoc communication link, and the like. The communication linkcan refer to direct communications or indirect communications betweenthe radiotherapy device controller 508 and the radiotherapy device 502,between the database(s) 514 and the EDIC calculator, between the userinterface 506 and the treatment plan optimizer 512, or any othercombination of the elements of the radiotherapy system 500, wherein theindirect communication occurs via at least one other device (e.g., arepeater, router, hub, and/or the like). The communication link canfacilitate unidirectional and/or bi-directional communication betweenthe various elements of the radiotherapy system 500. In someembodiments, the communication link is, includes, or is included in awired network, a wireless network, or a combination of wired andwireless networks. Illustrative networks include any number of differenttypes of communication networks such as, a short messaging service(SMS), a local area network (LAN), a wireless LAN (WLAN), a wide areanetwork (WAN), the Internet, a peer-to-peer (P2P) network, or othersuitable networks. The network may include a combination of multiplenetworks. In some embodiments, for example, the radiotherapy system isaccessible via the Internet (e.g., the radiotherapy system mayfacilitate a web-based RT treatment plan optimization/selectionservice), and a user may transmit one or more possible RT treatmentplans to the radiotherapy system to optimize/select an adjusted RTtreatment plan (i.e., a patient-specific radiotherapy treatment plan).

In some embodiments, the system controller 520 causes the EDICcalculator to access the database 514 and/or I/O device 516 to obtainone or more initial RT treatment plans via a communication link.Intermediary RT treatment plan data from the database(s) 514 can beweb-based, cloud based, or local. In some embodiments the initial RTtreatment plan data and/or the databases 514 are retrieved from a thirdparty, produced by the user, or some combination thereof. The databases514 can be any collection of information providing, for example,information regarding common RT treatment plans, patient data, and thelike.

The following statements further describe various embodiments of thedisclosure.

Statement 1. A radiotherapy system comprising a radiotherapy deviceconfigured to deliver a radiotherapy to a patient and a treatmentcontroller having one or more processors and a non-transitory, tangiblestorage medium containing instructions that, when executed, cause theone or more processors to:

-   -   calculate from an initial radiotherapy treatment plan for a        patient, an equivalent uniform dose (EUD) for each organ in a        target irradiation area in the patient; calculate an effective        dose of radiation to circulating immune cells in blood (EDIC)        for the patient by summing all EUDs for all organs in the target        irradiation area; and generate a new patient-specific        radiotherapy treatment plan for the patient, wherein the new        patient-specific radiotherapy treatment plan decreases a        calculated EDIC relative to the initial radiotherapy treatment        plan,    -   wherein the radiotherapy device is configured to deliver        radiotherapy to the patient according to the new        patient-specific radiotherapy treatment plan.

Statement 2. The radiotherapy system of statement 1, wherein the newpatient-specific radiotherapy treatment plan further maximizes aradiation dose to a tumor.

Statement 3. The radiotherapy system of statement 1 or statement 2,wherein the new patient-specific radiotherapy treatment plan results ina calculated EDIC of 6.0 Gy or less.

Statement 4. The radiotherapy system of any one of statements 1-4,wherein the new patient-specific radiotherapy treatment plan isgenerated by adjusting the initial radiotherapy treatment plan by one ormore of:

-   -   incorporating a hypofractionated radiotherapy treatment regimen;    -   decreasing radiation delivery time;    -   adjusting at least one of: beam energies, beam directions, and        number of beams;    -   optimizing collimator margins;    -   incorporating an intensity-modulated radiotherapy planning        technique;    -   incorporating an image-guided adaptive therapy technique;    -   incorporating a proton therapy technique;    -   dose de-escalation; and    -   margin reduction.

Statement 5. The radiotherapy system of any one of statements 1-4,wherein the new patient-specific radiotherapy treatment plan isgenerated by adjusting the initial radiotherapy treatment plan by one ormore of:

-   -   increasing radiation delivery time;    -   adjusting at least one of: beam energies, beam directions, and        number of beams;    -   optimizing collimator margins;    -   dose escalation; and    -   increasing margins.

Statement 6. The radiotherapy system of any one of statements 1-5,wherein the EUD for each organ is calculated from a dose volumehistogram (DVH) for blood circulating through the organ, wherein the DVHafter an ith radiation fraction represents a percentage of total bodyblood volume that receives a particular radiation dose when in the organduring the radiation fractions.

Statement 7. The radiotherapy system of any one of statements 1-5,wherein the EUD for each organ is calculated as a product of apercentage of blood volume B % in an organ, a mean organ dose for theorgan, a dose effectiveness factor, and one half a quotient of n and aradiation saturation fraction factor, wherein n is a number of radiationfractions to be administered.

Statement 8. The radiotherapy system of any one of statements 1-5,wherein the EUD for each organ is calculated as a product of apercentage of blood volume B % in an organ and a mean organ dose for theorgan, wherein B % is an amount of blood contained in the organ at anytime relative to a total body blood volume, a number of radiationfractions to be administered to the patient is equal to or greater thana quotient of a radiation saturation fraction factor and V %, wherein V% is a percentage of blood that receives a radiation dose as the bloodpasses through the organ.

Statement 9. The radiotherapy system of any one of the statementsherein, wherein the target irradiation area is a thoracic area, and theEDIC is calculated by summing the EUDs for the patient's lungs, heart,thoracic great vessels, and small vessels and capillaries in thethoracic area. The DVH of small vessels and capillaries can berepresented by the DVH of the total body.

Statement 10. The radiotherapy system of any one of the statementsherein, further comprising one or more imaging modalities.

Statement 11. The radiotherapy system of any one of the statementsherein, wherein the instructions, when executed, cause the one or moreprocessors to generate one or more additional new patient-specificradiotherapy treatment plans for the patient during delivery of the newpatient-specific radiotherapy treatment plan to the patient.

Statement 12. A method for treating a patient, the method comprising:

-   -   calculating from an initial radiotherapy treatment plan for the        patient, an equivalent uniform dose (EUD) for each organ in a        target irradiation area in the patient;    -   calculating an effective dose of radiation to circulating immune        cells in blood (EDIC) for the patient by summing all EUDs for        all organs in the target irradiation area;    -   generating a new patient-specific radiotherapy treatment plan        for the patient, wherein the new patient-specific radiotherapy        treatment plan decreases a calculated EDIC relative to the        initial radiotherapy treatment plan; and    -   delivering radiotherapy to the patient according to the new        patient-specific radiotherapy treatment plan.

Statement 13. The method of statement 12, wherein the newpatient-specific radiotherapy treatment plan further maximizes aradiation dose to a tumor.

Statement 14. The method of statement 12 or statement 13, wherein thenew patient-specific radiotherapy treatment plan results in a calculatedEDIC of 6.0 Gy or less.

Statement 15. The method of any one of statements 12-14, wherein the newpatient-specific radiotherapy treatment plan is generated by adjustingthe initial radiotherapy treatment plan by one or more of:

-   -   incorporating a hypofractionated radiotherapy treatment regimen;    -   decreasing radiation delivery time;    -   adjusting at least one of: beam energies, beam directions, and        number of beams;    -   optimizing collimator margins;    -   incorporating an intensity-modulated radiotherapy planning        technique;    -   incorporating an image-guided adaptive therapy technique;    -   incorporating a proton therapy technique;    -   dose de-escalation; and    -   margin reduction.

Statement 16. The method of any one of statements 12-14, wherein the newpatient-specific radiotherapy treatment plan is generated by amendingthe initial radiotherapy treatment plan by one or more of:

-   -   increasing radiation delivery time;    -   adjusting at least one of: beam energies, beam directions, and        number of beams;    -   optimizing collimator margins;    -   dose escalation; and    -   increasing margins.

Statement 17. The method of any one of statements 12-16, wherein the EUDfor each organ is calculated from a dose volume histogram (DVH) forblood circulating through the organ, wherein the DVH after an ithradiation fraction represents a percentage of total body blood volumethat receives a particular radiation dose when in the organ during theradiation fractions.

Statement 18. The method of any one of statements 12-16, wherein the EUDfor each organ is calculated as a product of a percentage of bloodvolume B % in an organ, a mean organ dose for the organ, a doseeffectiveness factor, and one half a quotient of n and a radiationsaturation fraction factor, wherein n is a number of radiation fractionsto be administered.

Statement 19. The method of any one of statements 12-16, wherein the EUDfor each organ is calculated as a product of a percentage of bloodvolume B % in an organ and a mean organ dose for the organ, wherein B %is an amount of blood contained in the organ at any time relative to atotal body blood volume, a number of radiation fractions to beadministered to the patient is equal to or greater than a quotient of aradiation saturation fraction factor and V %, wherein V % is apercentage of blood that receive a radiation dose as the blood passesthrough the organ.

Statement 20. The method of treatment of any one of the statementsherein, wherein the target irradiation area is a thoracic area, and theEDIC is calculated by summing the EUDs for the patient's lungs, heart,thoracic great vessels, and small vessels and capillaries in thethoracic area.

Statement 21. The method of treatment of any one of the statementsherein, further comprising acquiring an image of the target irradiationarea in the patient utilizing at least one imaging modality.

Statement 22. The method of treatment of any one of the statementsherein, further comprising generating one or more additional newpatient-specific radiotherapy treatment plans for the patient duringdelivery of the new patient-specific radiotherapy treatment plan to thepatient, stopping delivery of the new patient-specific radiotherapytreatment plan to the patient, and delivering one of the one or moreadditional new patient-specific radiotherapy treatment plans.

Statement 23. A radiotherapy system comprising a radiotherapy deviceconfigured to deliver a radiotherapy in accordance with a radiotherapyplan and one or more processors programmed to perform the twocalculating steps and the generating step of the method according to anyone of statements 12-16.

Statement 24. A non-transitory computer-readable medium havinginstructions stored thereon for causing one or more processors toperform the two calculating steps and the generating step of the methodaccording to any one of statements 12-16.

Statement 25. A radiotherapy treatment controller comprising one or moreprocessors and a non-transitory, tangible storage medium containinginstructions that, when executed, cause the one or more processors to:

-   -   calculate from an initial radiotherapy treatment plan for a        patient, an equivalent uniform dose (EUD) for each organ in a        target irradiation area in the patient;    -   calculate an effective dose of radiation to circulating immune        cells in blood (EDIC) for the patient by summing all EUDs for        all organs in the target irradiation area; and    -   generate a new patient-specific radiotherapy treatment plan for        the patient, wherein the new patient-specific radiotherapy        treatment plan decreases a calculated EDIC relative to the        initial radiotherapy treatment plan.

Statement 26. The radiotherapy treatment controller of statement 25,wherein the radiotherapy treatment controller is communicatively coupledto a radiotherapy device configured to deliver radiotherapy to thepatient.

Statement 27. The radiotherapy treatment controller of statement 25 orstatement 26, wherein the radiotherapy device is configured to deliverthe radiotherapy to the patient according to the new patient-specificradiotherapy treatment plan.

Statement 28. The radiotherapy treatment controller of any one ofstatements 25-27, wherein the new patient-specific radiotherapytreatment plan further maximizes a radiation dose to a tumor.

Statement 29. The radiotherapy treatment controller of any one ofstatements 25-28, wherein the new patient-specific radiotherapytreatment plan results in a calculated EDIC of 6.0 Gy or less.

Statement 30. The radiotherapy treatment controller of any one ofstatements 25-29, wherein the new patient-specific radiotherapytreatment plan is generated by adjusting the initial radiotherapytreatment plan by one or more of:

-   -   incorporating a hypofractionated radiotherapy treatment regimen;    -   decreasing radiation delivery time;    -   adjusting at least one of: beam energies, beam directions, and        number of beams;    -   optimizing collimator margins;    -   incorporating an intensity-modulated radiotherapy planning        technique;    -   incorporating an image-guided adaptive therapy technique;    -   incorporating a proton therapy technique;    -   dose de-escalation; and    -   margin reduction.

Statement 31. The radiotherapy treatment controller of any one ofstatements 25-29, wherein the new patient-specific radiotherapytreatment plan is generated by adjusting the initial radiotherapytreatment plan by one or more of:

-   -   increasing radiation delivery time;    -   adjusting at least one of: beam energies, beam directions, and        number of beams;    -   optimizing collimator margins;    -   dose escalation; and    -   increasing margins.

Statement 32. The radiotherapy treatment controller of any one ofstatements 25-31, wherein the EUD for each organ is calculated from adose volume histogram (DVH) for blood circulating through the organ,wherein the DVH after an ith radiation fraction represents a percentageof total body blood volume that receives a particular radiation dosewhen in the organ during the radiation fractions.

Statement 33. The radiotherapy treatment controller of any one ofstatements 25-31, wherein the EUD for each organ is calculated as aproduct of a percentage of blood volume B % in an organ, a mean organdose for the organ, a dose effectiveness factor, and one half a quotientof n and a radiation saturation fraction factor, wherein n is a numberof radiation fractions to be administered.

Statement 34. The radiotherapy treatment controller of any one ofstatements 25-31, wherein the EUD for each organ is calculated as aproduct of a percentage of blood volume B % in an organ and a mean organdose for the organ, wherein B % is an amount of blood contained in theorgan at any time relative to a total body blood volume, a number ofradiation fractions to be administered to the patient is equal to orgreater than a quotient of a radiation saturation fraction factor and V%, wherein V % is a percentage of blood that receives a radiation doseas the blood passes through the organ.

Statement 35. The radiotherapy treatment controller of any one ofstatements 25-34, wherein the target irradiation area is a thoracicarea, and the EDIC is calculated by summing the EUDs for the patient'slungs, heart, thoracic great vessels, and small vessels and capillariesin the thoracic area.

EXAMPLES

The materials, methods, and embodiments described herein are furtherdefined in the following Examples. Certain embodiments are defined inthe Examples herein. It should be understood that these Examples, whileindicating certain embodiments, are given by way of illustration only.From the disclosure herein and these Examples, one skilled in the artcan ascertain the essential characteristics of this invention, andwithout departing from the spirit and scope thereof, can make variouschanges and modifications of the invention to adapt it to various usagesand conditions.

Example 1—Higher Radiation Dose to Immune System Correlates with PoorerSurvival in Patients With Stage III Non-Small Cell Lung Cancer

In one example of the embodiments described herein, it is demonstratedthat higher radiation doses to circulating immune cells results inpoorer overall survival in patients with stage III non-small cell lungcancer.

Lung cancer is the leading cause of cancer-related death worldwide. Over85% of lung cancers are non-small cell lung cancer (NSCLC), and 40% arestage III. Standard care for unresectable stage III NSCLC isradiotherapy (RT) with concurrent chemotherapy. Despite advances in RTtechnology, treatment outcome remains suboptimal, and local diseaseprogression is a major cause of death. Intensifying local therapy withRT dose escalation was therefore believed to improve local tumor controland survival. RTOG 0617 was designed to test the effects of radiationdose escalation in locally advanced NSCLC and randomized patients tohigh-dose (74 Gy) versus low-dose (60 Gy) chemoradiation (Bradley etal., Lancet Oncol. 2015 Feb., 16(2):187-199). However, the results ofthe RTOG study unexpectedly revealed significantly worse overallsurvival (OS) with the high-dose regimen.

Recent reports suggest that radiation-induced tumor cell killing canactivate the immune system by releasing tumor specific antigens.Preclinical studies have demonstrated that the immune system plays a keyrole in tumor control during RT. Treatments with RT alone or RT combinedwith immunotherapy controlled the tumors in immunocompetent mice, butnot in immune-deficient mice. An abscopal effect (i.e., shrinkage ofun-irradiated tumors far apart from the RT fields) has been observed inanimal studies and in single-patient case report. While theseobservations suggest that RT may augment anti-tumor immunity in certainsettings, RT is also well known to have immunosuppressive effects. Oneof the most common and clinically significant features ofradiation-induced immunosuppression is radiation-induced lymphopenia,which has been repeatedly associated with poorer survival in severalstudies as well as in a recent pooled analysis of multipletreatment-refractory solid tumors.

In the study described in this example, it was hypothesized thatexcessive RT dose to the immune system impairs various immune functionsincluding anti-tumor immunity and leads to decreasing patient diseasecontrol and survival. To test this hypothesis, a model was firstdeveloped to compute the effective dose to immune cells (EDIC) duringthe entire RT course, and the relationship between EDIC and the risk oftumor progression and death was evaluated. The RTOG 0617 trial provideda setting for testing this hypothesis, as detailed dosimetric andsurvival data were available for nearly all patients enrolled in thislarge phase III cooperative group trial.

Patient, Clinical Data, and Dosimetry Data

RTOG 0617 was a phase 3 trial for unresectable stage III NSCLC (Bradleyet al., Lancet Oncol. 2015 Feb., 16(2):187-199). All patients receivedconformal radiotherapy with concurrent and consolidation chemotherapy(carboplatin and paclitaxel). The treatment options of RT dose (60 Gyvs. 74 Gy) and cetuximab (yes vs. no) were used in the two-by-twofactorial randomized design. All eligible patients who had retrievableRT plans and received at least 51 Gy were included in the presentanalysis. Clinical factors analyzed for survival and tumor controlincluded baseline Zubrod performance status, use of positron emissiontomography (PET) during staging, tumor histology, age at randomization,gender, race, tumor locations, weight loss, smoking history, gross tumorvolume (GTV), and whether patients received full courses ofchemotherapy. Conventional radiation dosimetry data such as mean lungdose (MLD), mean heart dose (MHD) and integral total dose (ITD) werealso included for modeling.

EDIC Computation

The immune system has not generally been considered as an organ at riskfor RT toxicity, and no guidelines presently exist to delineate theimmune system for the purposes of RT planning. In this example andthroughout the present disclosure, lymphocytes are considered as themain immune cell of interest, as lymphocytes are the primary effectorcells in antitumor immunity. Furthermore, radiation-induced lymphopeniahas been implicated as an important biomarker of worse outcomes inpatients undergoing RT. Under normal conditions, lymphocytes originatein the bone marrow and/or thymus and circulate through the body via bothblood vessels and lymphatic ducts. Lymphocytes are trafficked throughthe secondary lymphatic organs (spleen and lymph nodes), and migrate totumor if an immune response is activated. It was also reported thatirradiation of circulating blood is a mechanism for inducing lymphopeniabecause it occurs after irradiation of tissues such as the breast andbrain that contain little marrow or lymphatic tissue. Therefore, theradiation dose to the blood was considered as a surrogate for EDIC, andit was demonstrated that EDIC can be simply estimated by equation 6 forpatients receiving ≥25 fractions of thoracic radiation:

$\begin{matrix}{{{EDIC} = {{B_{1}\%*{MLD}} + {B_{2}\%*{MHD}} + {\left\lbrack {{B_{3}\%} + {B_{4}\%*k_{1}*\left( \frac{n}{45} \right)^{\frac{1}{2}}}} \right\rbrack*{{ITD}/\left( {6{1.8}*10^{3}} \right)}}}},} & (6)\end{matrix}$wherein B1%=0.12, B2%=0.08, B3%=0.45 and B4%=0.35 represent thepercentage of blood volume within the four major blood-containing organs(lung, heart, great vessels, and small vessels/capillaries in all otherorgans) of the total blood volume in the body, respectively, k1=0.85 isa dose effectiveness factor for the small vessels/capillaries, and61.8*103 (cm³) is the average total body volume, assuming average weightand density of 70 lps/63 kg and 1.02 g/cm³. A detailed derivation ofthis equation is provided in the present disclosure.Outcomes and Statistical Considerations

Risks of death and progressive disease were quantified through overallsurvival (OS), progression-free survival (PFS) and localprogression-free survival (LPFS). They were analyzed as time-to-eventdata and calculated from the date of randomization to the date ofrespective event or last follow-up. The OS event was death due to anycause; the PFS event was the first occurrence of any progression ordeath; the LPFS event was the first occurrence of local failure ordeath. These rates were estimated using the Kaplan-Meier method, and thedistributions between different groups were compared using the log-ranktest. Cox proportional hazards models were used to evaluate therelationship between EDIC and other factors with OS, PFS and LPFS.Because EDIC was derived from the combination of MLD, MHD and ITD, thesevariables were evaluated individually under multivariable analyses toavoid potential collinearity. The functional forms of EDIC in the Coxmodels were explored both linearly and using restricted cubic splines.To illustrate the non-linear functional form of EDIC in the Cox model,EDIC was also categorized based on quartiles and absolute EDIC values.The proportionality assumption was graphically assessed using plots oflog(−log[survival]) versus log of survival time, and tested using aformal test based on the Schoenfeld residuals. Interaction terms (e.g.,potentially differential effects of EDIC on outcomes by different levelsof patient characteristics) were also examined using the Wald test.

Results

Patient Characteristics

Of 495 eligible patients enrolled in the RTOG 0617 study, 466 hadretrievable RT plans. Ten patients were excluded from this analysis forthe following reasons: RT plan missed the target (n=1), incorrectlyarchived RT plan (exactly same plan for 2 different patients) (n=4), ortotal dose received was ≤51 Gy (n=5). Of the 456 remaining patients, 256and 200 were originally assigned to the standard (60 Gy) and high dosearms (74 Gy), respectively; 261 patients received 60 Gy (including 5patients originally assigned to the high dose arm), 165 received 74 Gy,4 received 52-58 Gy, 12 received 62-66 Gy, and 6 received 67-72 Gy. Thepatients were categorized according to the actual dose received, with adose of >67 Gy defined as high dose. Based on this definition, 285 and171 patients were placed into the low- and high-dose groups,respectively.

Median follow-up time for patients alive at the last evaluation was 30.3months (range 2.5-61.5 months). Demographic, clinical, and dosimetricdata are summarized in Table 2. EDIC was calculated for all 456patients. Median EDIC was 5.58 Gy (range 2.05-12.20 Gy) for the low dosegroup, 6.34 Gy (2.14-11.59 Gy) for the high dose group, and 5.94 Gy(2.05-12.20 Gy) for all patients.

TABLE 2 Patient Characteristic and their difference between the twotumor dose groups. P <0.05 denotes that there is a significantdifference between the two groups Characteristics Dose <67 Gy (n = 285)Dose ≥ 67 Gy (n = 171) Total (n = 456) p-Value Age 64 (37-82) 64 (41-84)64 (37-84) 0.89 Gender 0.43 Male 174 (61%) 98 (57%) 272 (60%) Female 111(39%) 73 (435) 184 (40%) Race 0.44 White 242 (85%) 152 (89%) 394 (86%)Black 31 (11%) 13 (8%) 44 (10%) Others 12 (4%) 6 (3%) 18 (4%) Zubrod0.90 0 170 (60%) 101 (59%) 271 (59%) 1 115 (40%) 70 (41%) 185 (41%)Histology 0.68 Squamous 122 (43%) 73 (43%) 195 (43%) Adeno 114 (40%) 65(38%) 179 (39%) Others 48 (17%) 33 (19%) 81 (18%) AJCC Stage 0.73 IIIa190 (67%) 111 (65%) 301 (66%) IIIb 94 (33%) 59 (35%) 153 (34%) RTTechnique 0.48 3D-CRT 153 (54%) 86 (50%) 239 (52%) IMRT 132 (46%) 85(50%) 217 (48%) PET Staging 0.37 No 23 (8%) 18 (11%) 41 (9%) Yes 262(92%) 153 (90%) 415 (91%) Tumor Location 0.48 LLL/central location 32(11%) 23 (14%) 55 (12%) Others 253 (89%) 148 (87%) 401 (88%) Weightloss/month 0 (0-9%) 0 (0-7%) 0 (0-9%) 0.99 Esophagitis Grade 0.03 Grade< 3 253 (89%) 139 (81%) 392 (86%) Grade ≥ 3 32 (11%) 32 (19%) 64 (14%)Received full Chemo 0.095 No 42 (15%) 16 (9%) 58 (13%) Yes 243 (85%) 155(91%) 398 (87%) GTV (cc) 92.7 (4.6-960.7) 93.7 (5.4-698.9) 92.7(4.6-961) 0.48 MLD (Gy) 17.4 (5.4-31.7) 20.1 (5.1-32.7) 18.4 (5.1-32.7)<0.0001 MHD (Gy) 13.2 (0-47.1) 12.6 (0.4-49.4) 12.7 (0-49.4) 0.45 ITD(Gy•liter) 206 (62-545) 244 (104-464) 218 (62-545) <0.0001 EDIC (Gy)5.58 (2.05-12.20) 6.34 (2.14-11.59) 5.94 (2.05-12.2) <0.0001Abbreviations: RT: Radiotherapy; 3D-CRT: 3-D conformal radiationtherapy; IMRT: intensity modulated radiation therapy; LLL: low leftlobe; GTV: gross tumor volume; MLD: mean lung dose; MHD: mean heartdose; ITD: integral total dose; EDIC: effective dose to the immunecells; OS: overall survival; PFS: Progression free survival; LPFS: Localregional progression free survival.Univariate Analysis for OS, PFS, and LPFS

When patients were re-categorized according to the dose actuallyreceived, the low-dose patients had marginally better OS and PFS, andsignificantly better LPFS than the high-dose patients. This tumor doseeffect was adjusted by stratifying it in the univariate analysis for allother potential prognostic factors. Gender, Zubrod performance status,tumor histology, smoking history, use of PET staging, AJCC stage werenot significantly associated with OS, PFS and LPFS, while the occurrenceof grade ≥3 esophagitis/dysphagia and completion of full course ofchemotherapy were significantly associated with OS, PFS and LPFS (Table3). Tumor location (central/lower left lobe vs. others) wassignificantly associated with OS only. All dosimetric factors, includingGTV, MLD, MHD, ITD and EDIC, were significantly associated with OS, PFSand LPFS, except ITD, which was only significantly associated with OS(Table 3).

TABLE 3 Univariate analysis stratified by actually received dose* OS PFSLPFS HR HR HR Variables (95% CI) p value (95% CI) p value (95% CI) pvalue Prescription 1.31 0.01 1.22 0.07 1.34 0.01 dose (1.04, 1.67)(0.98, 1.51) (1.07-1.67) Actual received 1.22 0.10 1.21 0.08 1.32 0.017dose (0.95, 1.56) (0.98, 1.50) (1.05, 1.65) Age 1.01 0.24  0.997 0.591.01 0.26 (0.99, 1.02) (0.99, 1.009) (0.99, 1.02) Gender 0.83 0.13 0.960.71 0.88 0.27 (0.65, 1.06) (0.77, 1.19) (0.70, 1.10) Zubrod 1.02 0.860.95 0.64 1.01 0.91 (0.80, 1.30) (0.76, 1.18) (0.81, 1.27) Histology1.13 0.34 1.02 0.87 1.19 0.12 (0.88, 1.43) (0.82, 1.26) (0.95, 1.49)Smoke History 0.72 0.22 0.79 0.32 0.80 0.37 (0.43, 1.21) (0.50, 1.26)(0.50, 1.30) RT Technique 0.89 0.33 1.04 0.74 1.06 0.64 (0.70, 1.13)(0.84, 1.28) (0.84, 1.32) PET Staging 0.76 0.16 0.87 0.45 0.83 0.34(0.52, 1.11) (0.61, 1.24) (0.58, 1.21) AJCC Stage 1.03 0.82 1.08 0.521.08 0.49 (0.80, 1.32) (0.86, 1.35) (0.86, 1.37) Tumor Location 1.490.02 1.21 0.25 1.33 0.09 (1.06, 2.09) (0.88, 1.66) (0.95, 1.84)Esophagitis 1.77 0.0003 1.72 0.0002 1.53 0.005 grade (1.30, 2.41) (1.29,2.28) (1/14. 2.06) Received full 0.64 0.009 0.72 0.03 0.70 0.03 Chemo(0.46, 0.90) (0.53, 0.97) (0.51, 0.97) GTV 1.21 0.0026 1.13 0.03 1.130.04 (1.07, 1.38) (1.01, 1.26) (1.01, 1.27) Mean Lung 1.05 0.0004 1.040.003 1.03 0.02 Dose (1.02, 1.09) (1.01, 1.07) (1.004, 1.06) Mean Heart1.02 <0.0001 1.01 0.004 1.02 0.0007 Dose (1.01, 1.03) (1.003, 1.02)(1.007, 1.03) Total Body  1.003 0.0004  1.001 0.11 1.002 0.03 Dose(1.001, 1.005) (1.00, 1.003) (1.00, 1.003) EDIC 1.18 <0.0001 1.10 0.0021.11 0.0009 (1.10, 1.26) (1.03, 1.16) (1.05, 1.18) *The effect of actualreceived dose has been stratified for all other factors in thisunivariate analysis except for the prescription dose and actuallyreceived dose. Abbreviations: RT: Radiotherapy; HR: Hazard ratio; CI:confident interval; GTV: gross tumor volume; EDIC: effective dose to theimmune cells; OS: overall survival; PFS: Progression free survival;LPFS: Local regional progression free survival.Multivariate Analysis for OS, PFS, and LPFS

The clinical and dosimetric factors that were identified of interestfrom univariate analysis were further studied using stratifiedmultivariable analyses according to the actual RT dose received for OS,PFS and LPFS in two different multivariate models: one without EDIC butwith MLD/MHD/ITD, and one with EDIC but without MLD/MHD/ITD. Theoccurrence of grade ≥3 esophagitis/dysphagia and completion ofchemotherapy remained significantly associated with OS, PFS and LPFS forboth models (Tables 4a-4c). In the OS model without EDIC, the MHD, MHDand ITD were no longer significant factors, and GTV remainedsignificant. While in the model with EDIC, EDIC was significantlyassociated with OS but the GTV was not (Table 4a). MLD and GTV weresignificantly associated with PFS (Table 4b), while MHD wassignificantly associated with LPFS (Table 4c) in the multivariablemodels without EDIC. While EDIC was not significantly associated withPFS, it was significantly associated with LPFS in the multivariablemodels (Tables 4b and 4c).

Tables 4a-4c. Stratified multivariable analyses according to the actualreceived RT dose.

TABLE 4a OS Without EDIC OS With EDIC Variables HR (95% CI) p-Value HR(95% CI) p-Value Tumor Location 1.42 (0.98, 2.05) 0.07 1.41 (0.98, 2.02)0.07 Gross tumor volume 1.16 (1.00, 1.34) 0.05 1.12 (0.98, 1.28) 0.09Esophagitis grade 1.53 (1.11, 2.11) 0.01 1.52 (1.10, 2.10) 0.012Received full Chemo 0.58 (0.41, 0.81) 0.0015 0.59 (0.42, 0.83) 0.003Mean lung dose 1.03 (0.998, 1.070) 0.07 Mean heart dose 1.008 (0.995,1.022) 0.21 Integral total dose 1.000 (0.998, 1.002) 0.93 EDIC 1.12(1.03, 1.21) 0.005

TABLE 4b PFS Without EDIC PFS With EDIC Variables HR (95% CI) p-Value HR(95% CI) p-Value Tumor Location 1.19 (0.84, 1.68) 0.33 1.20 (0.85, 1.68)0.30 Gross tumor volume 1.15 (1.01, 1.32) 0.04 1.08 (0.96, 1.21) 0.20Esophagitis grade 1.64 (1.22, 2.21) 0.001 1.60 (1.19, 2.15) 0.002Received full Chemo 0.63 (0.46, 0.86) 0.003 0.66 (0.49, 0.90) 0.009 Meanlung dose 1.04 (1.006, 1.071) 0.02 Mean heart dose 1.005 (0.992, 1.017)0.47 Integral total dose 0.998 (0.996, 1.000) 0.10 EDIC 1.05 (0.98,1.12) 0.17

TABLE 4c LPFS Without EDIC LPFS With EDIC Variables HR (95% CI) p-ValueHR (95% CI) p-Value Gross tumor volume 1.09 (0.97, 1.23) 0.13 1.07(0.95, 1.20) 0.29 Esophagitis grade 1.36 (1.00, 1.85) 0.05 1.37 (1.00,1.86) 0.05 Received full Chemo 0.66 (0.48, 0.91) 0.012 0.67 (0.48, 0.92)0.013 Mean lung dose 1.01 (0.98, 1.04) 0.51 Mean heart dose 1.012(1.000, 1.024) 0.045 EDIC 1.09 (1.01, 1.16) 0.02

Abbreviations: HR: Hazard ratio; CI: confident interval; EDIC: effectivedose to the immune cells; OS: overall survival; PFS: Progression freesurvival; LPFS: Local regional progression free survival.

Relationship Between EDIC and OS

To further analyze the relationship between EDIC and OS, patients weredivided into four quartiles according to EDIC (FIG. 6A) as well as intosix groups based on absolute EDIC (using 1.5-Gy increments; FIG. 6B).The Kaplan-Meier curves shown in FIG. 6 depict a strong inverserelationship between OS and EDIC (i.e., as EDIC increases, OSdecreases). However, the relationship between EDIC and OS is non-linear,as shown in the hazard-versus-EDIC curve created through nonparametricsmoothing using restricted cubic splines (FIG. 7A). This analysis showsthat hazard rates increase with increasing EDIC when EDIC is less than6.0 Gy or larger than 8.0 Gy. Univariate Cox models with stratifiedtumor dose demonstrated that death hazard increased by 23%/Gy (1.07,1.41), p=0.003 with increasing EDIC when EDIC<6.0, and by 37%/Gy (1.14,1.64), p=0.0007 when EDIC>8 Gy. However, this curve is relatively flatwhen EDIC is between 6.0-8.0 Gy.

This non-linear relationship is also illustrated by the survival-doseresponse curve for 2-year OS versus EDIC (FIG. 7B). The 6 data pointswere determined from the data of 6 subgroups in FIG. 6B, with thehorizontal axis of each point being the average EDIC for thecorresponding subgroup. The data are well fitted by an OS model composedof two normal tissue complication probability (NTCP) components:

${OS} = {{0.7}4*\left\lbrack {1 - \frac{{0.3}9}{1 + \left( \frac{4.5}{EDIC} \right)^{6}}} \right\rbrack*\left\lbrack {1 - \frac{1}{1 + \left( \frac{9.9}{EDIC} \right)^{12}}} \right\rbrack}$with D₅₀ being 4.5 and 9.9 Gy, respectively, for the two NTCPcomponents, suggesting two responding mechanisms or structures for therelationship. Alternatively, the survival-dose response can also besimply described by a combined linear model with 3 parts: 1) EDIC <6.0Gy, 2-year OS decreases with increasing EDIC at a slope of 8%/Gy; 2)EDIC between 6.0-8.0 Gy, OS keeps flat; 3) EDIC>8.0 Gy, 2-year OSdecreases with increasing EDIC at a slope of 12%/Gy.

A direct clinical implication of this study is that circulating immunecells should be considered as a critical organ at risk and that EDICshould be limited in routine clinical practice. The data suggest thatpatients with either high (>8.0 Gy) or low EDIC (<6.0 Gy) can benefitfrom this finding. Patients at the high EDIC levels would be expected toderive the largest benefit (12% expected OS improvement with a 1-Gy EDICreduction among patients with high EDIC comparing 8% for the low-EDICgroup). Patients with intermediate EDIC (6-8 Gy) may have limitedbenefits unless a substantial reduction of EDIC could be achieved (i.e.,6.0 Gy or less).

The present study is the first to calculated EDIC and demonstrate thatEDIC is significantly and strongly associated with localprogression-free survival and overall survival among patients withunresectable stage III NSCLC treated with concurrent chemoradiation. Thefindings indicate that radiation toxicity to the immune system affectstreatment outcomes.

What is claimed is:
 1. A radiotherapy system comprising a radiotherapydevice configured to deliver a radiotherapy to a patient and a treatmentcontroller having one or more processors and a non-transitory, tangiblestorage medium containing instructions that, when executed, cause theone or more processors to: calculate from an initial radiotherapytreatment plan for a patient, an equivalent uniform dose (EUD) for eachorgan in a target irradiation area in the patient; calculate aneffective dose of radiation to circulating immune cells in blood (EDIC)for the patient by summing all EUDs for all organs in the targetirradiation area; and generate a new patient-specific radiotherapytreatment plan for the patient, wherein the new patient-specificradiotherapy treatment plan decreases a calculated EDIC relative to theinitial radiotherapy treatment plan, wherein the radiotherapy device isconfigured to deliver radiotherapy to the patient according to the newpatient-specific radiotherapy treatment plan.
 2. The radiotherapy systemof claim 1, wherein the new patient-specific radiotherapy treatment planfurther maximizes a radiation dose to a tumor.
 3. The radiotherapysystem of claim 2, wherein the new patient-specific radiotherapytreatment plan is generated by adjusting the initial radiotherapytreatment plan by one or more of: increasing radiation delivery time;adjusting at least one of: beam energies, beam directions, and number ofbeams; optimizing collimator margins; dose escalation; and increasingmargins.
 4. The radiotherapy system of claim 1, wherein the newpatient-specific radiotherapy treatment plan results in a calculatedEDIC of 6.0 Gy or less.
 5. The radiotherapy system of claim 1, whereinthe new patient-specific radiotherapy treatment plan is generated byadjusting the initial radiotherapy treatment plan by one or more of:incorporating a hypofractionated radiotherapy treatment regimen;decreasing radiation delivery time; adjusting at least one of: beamenergies, beam directions, and number of beams; optimizing collimatormargins; incorporating an intensity-modulated radiotherapy planningtechnique; incorporating an image-guided adaptive therapy technique;incorporating a proton therapy technique; dose de-escalation; and marginreduction.
 6. The radiotherapy system of claim 1, wherein the EUD foreach organ is calculated from a dose volume histogram (DVH) for bloodcirculating through the organ, wherein the DVH after an ith radiationfraction represents a percentage of total body blood volume thatreceives a particular radiation dose when in the organ during theradiation fractions.
 7. The radiotherapy system of claim 1, wherein theEUD for each organ is calculated as a product of a percentage of bloodvolume B % in an organ, a mean organ dose for the organ, a doseeffectiveness factor, and one half a quotient of n and a radiationsaturation fraction factor, wherein n is a number of radiation fractionsto be administered.
 8. The radiotherapy system of claim 1, wherein theEUD for each organ is calculated as a product of a percentage of bloodvolume B % in an organ and a mean organ dose for the organ, wherein B %is an amount of blood contained in the organ at any time relative to atotal body blood volume, a number of radiation fractions to beadministered to the patient is equal to or greater than a quotient of aradiation saturation fraction factor and V %, wherein V % is apercentage of blood that receives a radiation dose as the blood passesthrough the organ.
 9. The radiotherapy system of claim 1, wherein thetarget irradiation area is a thoracic area, and the EDIC is calculatedby summing the EUDs for the patient's lungs, heart, thoracic greatvessels, and small vessels and capillaries in the thoracic area.
 10. Theradiotherapy system of claim 1, further comprising one or more imagingmodalities.
 11. The radiotherapy system of claim 1, wherein theinstructions, when executed, cause the one or more processors togenerate one or more additional new patient-specific radiotherapytreatment plans for the patient during delivery of the newpatient-specific radiotherapy treatment plan to the patient.
 12. Amethod for treating a patient, the method comprising: calculating froman initial radiotherapy treatment plan for the patient, an equivalentuniform dose (EUD) for each organ in a target irradiation area in thepatient; calculating an effective dose of radiation to circulatingimmune cells in blood (EDIC) for the patient by summing all EUDs for allorgans in the target irradiation area; generating a new patient-specificradiotherapy treatment plan for the patient, wherein the newpatient-specific radiotherapy treatment plan decreases a calculated EDICrelative to the initial radiotherapy treatment plan; and deliveringradiotherapy to the patient according to the new patient-specificradiotherapy treatment plan.
 13. The method of claim 12, wherein the newpatient-specific radiotherapy treatment plan further maximizes aradiation dose to a tumor.
 14. The method of claim 13, wherein the newpatient-specific radiotherapy treatment plan is generated by amendingthe initial radiotherapy treatment plan by one or more of: increasingradiation delivery time; adjusting at least one of: beam energies, beamdirections, and number of beams; optimizing collimator margins; doseescalation; and increasing margins.
 15. The method of claim 12, whereinthe new patient-specific radiotherapy treatment plan results in acalculated EDIC of 6.0 Gy or less.
 16. The method of claim 12, whereinthe new patient-specific radiotherapy treatment plan is generated byadjusting the initial radiotherapy treatment plan by one or more of:incorporating a hypofractionated radiotherapy treatment regimen;decreasing radiation delivery time; adjusting at least one of: beamenergies, beam directions, and number of beams; optimizing collimatormargins; incorporating an intensity-modulated radiotherapy planningtechnique; incorporating an image-guided adaptive therapy technique;incorporating a proton therapy technique; dose de-escalation; and marginreduction.
 17. The method of claim 12, wherein the EUD for each organ iscalculated from a dose volume histogram (DVH) for blood circulatingthrough the organ, wherein the DVH after an ith radiation fractionrepresents a percentage of total body blood volume that receives aparticular radiation dose when in the organ during the radiationfractions.
 18. The method of claim 12, wherein the EUD for each organ iscalculated as a product of a percentage of blood volume B % in an organ,a mean organ dose for the organ, a dose effectiveness factor, and onehalf a quotient of n and a radiation saturation fraction factor, whereinn is a number of radiation fractions to be administered.
 19. The methodof claim 12, wherein the EUD for each organ is calculated as a productof a percentage of blood volume B % in an organ and a mean organ dosefor the organ, wherein B % is an amount of blood contained in the organat any time relative to a total body blood volume, a number of radiationfractions to be administered to the patient is equal to or greater thana quotient of a radiation saturation fraction factor and V %, wherein V% is a percentage of blood that receives a radiation dose as the bloodpasses through the organ.
 20. The method of claim 12, wherein the targetirradiation area is a thoracic area, and the EDIC is calculated bysumming the EUDs for the patient's lungs, heart, thoracic great vessels,and small vessels and capillaries in the thoracic area.
 21. The methodof claim 12, further comprising acquiring an image of the targetirradiation area in the patient utilizing at least one imaging modality.22. The method of claim 12, further comprising generating one or moreadditional new patient-specific radiotherapy treatment plans for thepatient during delivery of the new patient-specific radiotherapytreatment plan to the patient, stopping delivery of the newpatient-specific radiotherapy treatment plan to the patient, anddelivering one of the one or more additional new patient-specificradiotherapy treatment plans.
 23. A radiotherapy system comprising aradiotherapy device configured to deliver a radiotherapy in accordancewith a radiotherapy plan and one or more processors programmed toperform the two calculating steps and the generating step of the methodaccording to claim
 12. 24. A non-transitory computer-readable mediumhaving instructions stored thereon for causing one or more processors toperform the two calculating steps and the generating step of the methodaccording to claim
 12. 25. A radiotherapy treatment controllercomprising one or more processors and a non-transitory, tangible storagemedium containing instructions that, when executed, cause the one ormore processors to: calculate from an initial radiotherapy treatmentplan for a patient, an equivalent uniform dose (EUD) for each organ in atarget irradiation area in the patient; calculate an effective dose ofradiation to circulating immune cells in blood (EDIC) for the patient bysumming all EUDs for all organs in the target irradiation area; andgenerate a new patient-specific radiotherapy treatment plan for thepatient, wherein the new patient-specific radiotherapy treatment plandecreases a calculated EDIC relative to the initial radiotherapytreatment plan.
 26. The radiotherapy treatment controller of claim 25,wherein the radiotherapy treatment controller is communicatively coupledto a radiotherapy device configured to deliver radiotherapy to thepatient.
 27. The radiotherapy treatment controller of claim 25, whereinthe radiotherapy device is configured to deliver the radiotherapy to thepatient according to the new patient-specific radiotherapy treatmentplan.
 28. The radiotherapy treatment controller of claim 25, wherein thenew patient-specific radiotherapy treatment plan further maximizes aradiation dose to a tumor.
 29. The radiotherapy treatment controller ofclaim 28, wherein the new patient-specific radiotherapy treatment planis generated by adjusting the initial radiotherapy treatment plan by oneor more of: increasing radiation delivery time; adjusting at least oneof: beam energies, beam directions, and number of beams; optimizingcollimator margins; dose escalation; and increasing margins.
 30. Theradiotherapy treatment controller of claim 25, wherein the newpatient-specific radiotherapy treatment plan results in a calculatedEDIC of 6.0 Gy or less.
 31. The radiotherapy treatment controller ofclaim 25, wherein the new patient-specific radiotherapy treatment planis generated by adjusting the initial radiotherapy treatment plan by oneor more of: incorporating a hypofractionated radiotherapy treatmentregimen; decreasing radiation delivery time; adjusting at least one of:beam energies, beam directions, and number of beams; optimizingcollimator margins; incorporating an intensity-modulated radiotherapyplanning technique; incorporating an image-guided adaptive therapytechnique; incorporating a proton therapy technique; dose de-escalation;and margin reduction.
 32. The radiotherapy treatment controller of claim25, wherein the EUD for each organ is calculated from a dose volumehistogram (DVH) for blood circulating through the organ, wherein the DVHafter an ith radiation fraction represents a percentage of total bodyblood volume that receives a particular radiation dose when in the organduring the radiation fractions.
 33. The radiotherapy treatmentcontroller of claim 25, wherein the EUD for each organ is calculated asa product of a percentage of blood volume B % in an organ, a mean organdose for the organ, a dose effectiveness factor, and one half a quotientof n and a radiation saturation fraction factor, wherein n is a numberof radiation fractions to be administered.
 34. The radiotherapytreatment controller of claim 25, wherein the EUD for each organ iscalculated as a product of a percentage of blood volume B % in an organand a mean organ dose for the organ, wherein B % is an amount of bloodcontained in the organ at any time relative to a total body bloodvolume, a number of radiation fractions to be administered to thepatient is equal to or greater than a quotient of a radiation saturationfraction factor and V %, wherein V % is a percentage of blood thatreceives a radiation dose as the blood passes through the organ.
 35. Theradiotherapy treatment controller of claim 25, wherein the targetirradiation area is a thoracic area, and the EDIC is calculated bysumming the EUDs for the patient's lungs, heart, thoracic great vessels,and small vessels and capillaries in the thoracic area.